# Handle parsing errors

Occasionally the LLM cannot determine what step to take because it outputs format in incorrect form to be handled by the output parser.
In this case, by default the agent errors. You can control this functionality by passing `handleParsingErrors` when initializing the agent
executor. This field can be a boolean, a string, or a function:

- Passing `true` will pass a generic error back to the LLM along with the parsing error text for a retry.
- Passing a string will return that value along with the parsing error text. This is helpful to steer the LLM in the right direction.
- Passing a function that takes an `OutputParserException` as a single argument allows you to run code in response to an error and return
  whatever string you'd like.

Here's an example where the model initially tries to set `"Reminder"` as the task type instead of an allowed value:

import CodeBlock from "@theme/CodeBlock";
import HandleParsingErrorExample from "@examples/agents/handle_parsing_error.ts";

import IntegrationInstallTooltip from "@mdx_components/integration_install_tooltip.mdx";

<IntegrationInstallTooltip></IntegrationInstallTooltip>

```bash npm2yarn
npm install @langchain/openai
```

<CodeBlock language="typescript">{HandleParsingErrorExample}</CodeBlock>

This is what the resulting trace looks like - note that the LLM retries before correctly choosing a matching enum:

https://smith.langchain.com/public/b00cede1-4aca-49de-896f-921d34a0b756/r
